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Economie

Research

Service

Rural

Development

Research

Report

Number 51

Rural Governments

Raising Revenues and

Feeling the Pressure c:

-9; :3

Richard J. Reeder
Rural Governments: Raising Revenues and Feeling the Pressure, by Richard J.

Reeder, Economic-Development Division, Economic Research Service, U.S.

Department of Agriculture. Rural Development Research Report No« 51«

ABSTRACT

Some local governments in nonmetro areas—especially those in the rural West

and in highly rural areas—experienced high levels of fiscal stress in the

midseventies that were associated with high and rising local taxes. These

local governments may be forced to cut back their rural development activities

in the eighties. This report looks at locally raised general revenues as a

percentage of local income to assess the fiscal pressures local governments

face in their efforts to raise revenues. Such revenue efforts increased in

many rural areas whose income and population declined. The high cost of

providing public services in sparsely populated areas contributed substantially

to rural fiscal pressure.

Keywords: Fiscal stress, local government finance, rural development, tax

effort, tax burden, fiscal trends, fiscal conditions, rural local governments.

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Washington, DC 20250 July 1985
CONTENTS

Page

SUMMARY. ili

INTRODUCTION 1

REVENUE EFFORT. 2

TRENDS IN REVENUE EFFORT. 7

Effects of Population Change 10

Effects of Income Change ....•...•.•... U

PLACES WITH HIGH AND RISING REVENUE EFFORT 14

IMPERFECTIONS IN THE MEASURE OF REVENUE EFFORT. 15

Local Government Responsibilities • 17

Low-Income Communities •.••....•.••...........•. 18

Tax Exporting 21

Findings of Regression Analysis 22

IMPLICATIONS. 23

REFERENCES 25

STATISTICAL APPENDIX: REGRESSION ANALYSIS 26

ACKNOWLEDGMENTS

The author wishes to thank the following individuals for their contributions to

this report: Eleanor L. Whitehead for preparing the maps; Mary DeNoble, Linda

Rail, Karen Levy, and Brenda Heggie for typing the manuscript, and Thomas F.

Stinson, Patrick J. Sullivan, Daniel Milkove, and J. Norman Reid for reviewing

the manuscript.
SUMMARY

Some local governments in nonmetro areas—especially those In the rural West

and in very rural areas—experienced high levels of fiscal stress in the

midseventies that were associated with high and rising local taxes. These

local governments may be forced to cut back their rural development activities

in the eighties. However, most local governments entered the eighties in sound

financial condition.

This report assesses fiscal pressures on local governments by looking at

locally raised revenues (taxes and user fees) as a percentage of local income.

It identifies those nonmetro areas most affected by such fiscal pressure. It

measures fiscal pressure by examining both the level of local government

revenue effort in 1977 and whether that level rose or fell from 1972 to 1977.

High (above average) revenue effort indicates local tax burdens were heavy in

1977. Rising revenue effort indicates tax rates increased in 1972-77. Areas

with both high and rising revenue effort experienced the most fiscal pressure.

Over 33 percent of the totally rural areas not adjacent to metro areas had both

high and rising local government revenue effort, in contrast to only 16 percent

of the less rural nonmetro areas. Efforts to raise revenues increased in about

half of the totally rural areas during the midseventies, particularly in areas

where income and population fell. The high cost of providing essential

government services in isolated, sparsely populated areas may explain why

totally rural areas experienced the greatest fiscal pressure.

Over a third of nonmetro counties in the West suffered fiscal strain from high

and rising revenue effort. Nonmetro areas in the South also faced fiscal

strain associated with rising revenue effort, but taxes there were lower than

in other regions.

Differences in tax exporting and importing (shifting taxes to nonresidents—

such as local property taxes paid by nonresident landowners), the division of

responsibilities between State and local governments, the degree to which

public services are provided by volunteers or the private sector, community

preferences, and incomes make any comparison of revenue effort extremely

difficult. For example, tax-exporting and tax-importing activities often

exaggerate revenue effort in the rural West and in highly rural areas.

The varying fiscal condition of local governments is an important issue to

Federal and State policymakers in the design and implementation of rural

development policies. Monitoring fiscal stress indicators, such as revenue

effort, is one way policymakers can appraise the fiscal pressure of local

governments in rural areas.
Rural Governments

Raising Revenues and

Feeling the Pressure

Richard J. Reeder

INTRODUCTION

Local governments played an increasingly important role in promoting rural

economic development in the seventies. Between 1972 and 1977, per capita

spending by nonmetro local governments grew 68 percent—an increase of 12

percent after adjustment for inflation (13, p. 47). 1/ Local government

spending stimulated local economies and provided public services needed to

accomnodate growing rural populations. Although the growth of local government

was important to rural development, raising revenues to finance it augmented

fiscal stress in many rural local governments.

This report identifies those rural places which are feeling the pressure of

revenue-raising activities by local governments. The midseventies, 1972 to

1977, were the most recent years for which data from the U.S. Census of

Governments were available for nonmetro counties. I use two indicators to

measure the fiscal pressure associated with raising revenues: the level of

revenue effort in 1977 and the change in revenue effort from 1972 to 1977. I

measure revenue effort as the percentage of local income taken in the form of

local government taxes and user charges. 1/

The fiscal pressure resulting from efforts to raise local government revenues

may have several effects. First, higher tax rates increase the cost of living

for residents and increase the cost of doing business for rural firms. The

economic wellbeing of the community may decline as a result, and inmigration of

people and firms may be discouraged. _3/ In the long run, therefore, higher

taxes may reduce the potential tax base available to local governments.

Second, higher taxes can reduce the flexibility of local government budgets

because they bring local government revenues closer to legal tax limitations.

Because local governments are legally required to maintain balanced budgets,

binding tax limitations can prevent a locality from responding effectively to

recessions, floods, and other emergencies requiring increased expenditures.

1/ Underscored numbers in parentheses refer to items in the references at

the end of the report.

1/ Revenue effort includes only general revenues; it excludes utility and

liquor store receipts so one can more easily compare different localities.

Federal and State aid are also excluded.

3_/ This result may not occur if higher taxes allow the local government to

increase important government services whose benefits are perceived as greater

than their costs.
Third, higher taxes can heighten political resistance to additional government

spending. If taxpayers perceive taxes as unjustly high, they may press for tax

rate reductions or restrictive tax limitation requirements, sometimes forcing

local governments to cut back on essential services. Fourth, taxpayers may

react to higher taxes by voting down bond referenda required to raise funds for

much needed infrastructure.

One can view revenue effort as a comprehensive local tax rate, thus

interpreting it as an indicator of either local revenue burden or fiscal

strain. The change in revenue effort is of interest because the phenomenon of

rising tax rates adds to perceived tax burdens. Thus, two communities may have

the same tax rates; however, if the first community's rates have risen recently

while the second community's rates have remained stable, the tax burden is more

noticeable in the first community. Trends in revenue effort also indicate the

direction of change in fiscal condition. Thus, a pattern of rising revenue

effort indicates the potential for fiscal stress in the future.

In this report, I compare revenue effort in different types of rural areas. I

distinguish six categories of nonmetro counties according to their degree of

rurality and metro-adjacency. Three degrees of rurality are defined for

nonmetro counties: (1) totally rural—fewer than 2,500 urban residents; (2)

less urbanized—2,500-19,999 urban residents; and (3) urbanized—20,000-50,000

urban residents, hj A nonmetro county may be considered either adjacent or

nonadjacent to metro areas. It is considered adjacent if it is contiguous to

one or more metro counties and if at least 1 percent of its residents commute

to the central city (or cities) of metro counties for employment; otherwise, it

is considered nonadjacent. 5J

I used Census tapes containing local government revenue data for U.S. county

areas, including the revenues of all levels of local governments located within

the county (county, municipalities, towns, townships, school districts, and

special districts), to compute the national averages for various types of rural

areas. j6/ To show regional variations, this study gives revenue effort

indicators for the four Census regions. Besides describing variations in rural

and regional efforts, I discuss some of the fiscal implications of these

variations and examine potential distortions in the measure of revenue effort.

REVENUE EFFORT

Revenue effort is one of a group of effort variables commonly used to indicate

fiscal pressure. In this study, revenue effort is computed as the percentage

_4/ Nonmetro counties are those outside Standard Metropolitan Statistical

Areas (SMSAs) as defined by the Office of Management and Budget for 1977. In

States with no county government jurisdictions, I use Census-defined "county

areas" as substitutes. Urban residents in nonmetro areas are defined as the

population that resides in incorporated and unincorporated towns and cities of

at least 2,500 inhabitants.

5J This report uses the categorization scheme used by Hines and others (5^,

p. 4), but I have updated it using 1977 Standard Metropolitan Statistical Area

definitions.

hj The revenue effort statistics presented in this report are unweighted

averages representing the average U.S. county area (excluding Alaska) within

any given category. Local government revenue data are from the Bureau of the

Census; local resident personal income data are from the Bureau of Economic

Analysis, U.S. Department of Commerce.
of local resident income which is raised in the form of local taxes, user

charges, and fees. Revenue effort Indicates the pressure (or burden) of taxes

and user charges on local tax bases. Thus, one should distinguish revenue

effort from measures of fiscal capacity and fiscal need which are also of

interest, but do not measure fiscal pressure (8^).

Empirical studies of local fiscal stress often examine revenue effort. Effort

variables are important in policymaking because Federal and State programs use

them when distributing aid to local governments. _7/ Many nonmetro areas with

relatively high revenue effort are likely to experience fiscal stress. To

identify the rural and regional characteristics of these places, I distinguish

among three levels of effort: very high, moderately high, and low. 8^/ Very

high effort is heavily concentrated in totally rural areas (fig. 1). In 1977,

25 percent of totally rural nonadjacent areas fell into the very high effort

category. Totally rural adjacent areas ranked second, with 13 percent of

counties having very high effort. Nine percent of less urbanized nonadjacent

areas had very high revenue effort, while only 3 percent of urbanized nonmetro

areas had very high effort.

TT The General Revenue Sharing (GRS) program is the largest and best-known

program using an effort variable in its aid distribution formula (14). Effort

factors are also used in various programs for State aid to local governments.

The Advisory Commission on Intergovernmental Relations identified 13 States

which use effort, capacity, or some other fiscal factor to distribute aid to

local governments (12, pp. 6-7).

BJ Areas with very high effort are nonmetro counties with revenue effort one

standard deviation or more above the average for nonmetro counties. Areas with

moderately high effort have effort less than one standard deviation above the

nonmetro average. Areas with low effort have effort below the nonmetro

average. The nonmetro average in 1977 was 6.3 percent of income (excluding

Alaska); the nonmetro standard deviation was 3.8 percent of income. Thus,

areas with very high effort had effort greater than 10.1 percent of income.

Areas with moderately high effort had effort between 6.3 and 10.1 percent of

income. Low effort areas had effort less than 6.3 percent of income.

Figure 1

Percentage of Counties with High Effort, by Type of Rurai Area, 1977

% of counties

60 r40

20

w^z^^

Nonadjacent

Urbanized

Adjacent

Less urbanized

Very

high effort

— Moderately

high effart

Totally rural
Describing variations in rural revenue effort is easier than explaining them.

The theory which may best explain these variations is the size economies

theory, which maintains that there are optimal community population size and

density where the per capita costs of providing public services are minimized. 9_/

Below this point, per capita costs Increase as population size and density

decrease. Although empirical evidence in municipal studies is not conclusive

on this subject, this theory fits the observed variations in revenue effort

well (^). According to this theory, lightly populated places, such as totally

rural areas, have suboptimal population size and density and can be expected to

have relatively high costs for providing public services. The high cost of

providing police protection or busing students to rural schools, for example,

would cause small, lightly populated communities to have higher revenue effort

and greater fiscal pressure than large, more densely populated communities

providing the same public services.

Metro-adjacent areas are more likely to have low revenue effort than

nonadjacent areas. This difference between adjacent and nonadjacent areas

occurs mainly in totally rural and less urbanized areas. About 66 percent of

adjacent totally rural areas had low effort, compared with only 47 percent for

nonadjacent totally rural areas. Over 70 percent of adjacent less urbanized

areas had low effort, compared with only 56 percent of nonadjacent less

urbanized areas. Urbanized areas do not differ between adjacent and

nonadjacent areas.

This distinction may also be explained by the size economies theory. Because of

their small population, less urbanized and totally rural areas may find it

economical to rely extensively on neighboring metropolitan governments for many

public- and private-sector services. This tendency may explain why adjacent

areas have lower revenue effort than nonadjacent areas which lack this

alternative. Urbanized adjacent areas, in contrast, may have sufficient

population to provide their own services economically, which may explain why

urbanized adjacent areas are as likely to have low revenue effort as urbanized

nonadjacent areas.

Totally rural areas show greater fiscal diversity. 10/ Although relatively few

totally rural areas have low revenue effort, the average effort for totally

rural, low effort counties is less than 4 percent of resident personal income,

substantially lower than the average for urbanized and less urbanized areas

(table 1). UJ In contrast, the average effort for totally rural, very high

effort counties is almost 15 percent of income—substantially higher than the

average for less rural areas.

Why do totally rural areas exhibit such diversity? One explanation is that

because revenue effort is related to income, the diverse income situations of

totally rural areas may lead to diverse fiscal conditions. A second

9/ In this report, size economies refer to economies related to both

population size and population density.

10/ The coefficient of variation for totally rural areas is double that for

less rural areas.

11/ This situation explains why the average revenue effort for totally rural

adjacent areas (6.0 percent of income) is less than that for less urbanized

nonadjacent areas (6.3 percent of income). Although the totally rural adjacent

category has a larger proportion of counties with very high effort (13 percent

of counties versus 9 percent of counties), about 66 percent of totally rural

adjacent counties have low effort, averaging only 3.7 percent of income.
Table 1—Revenue effort level for nonmetro county areas, 1977 1/

: Low effort Moderately higji effort Very high effort All areas

: Share : Average Share : Average : Share : Average : Share : Average

Area : of : effort of : effort of : effort of : effort

: counties counties : counties Î counties

Percent

Urbanized adjacent . 64 4.6 33 7.7 3 11.6 100 5.8

Urbanized nonadjacent Î 62 4.5 35 7.4 3 11.7 100 5.7

Less urbanized

adjaœnt ¡ 72 4.4 24 7.6 4 11.7 100 5.4

Less urbanized

nonadjacent 56 4.4 34 7.8 9 12.3 100 6.3

Totally rural

adjacent 66 3.7 21 7.8 13 14.4 100 6.0

Totally rural

nonadjacent 47 3.9 30 8.0 24 15.0 100 7.7

Kegions:

Northeast 52 4.6 41 7.7 8 13.2 100 6.5

North C>entral 48 5.0 40 7.7 12 12.6 100 7.0

South 79 3.8 16 7.6 5 15.7 100 5.0

Vfest 30 4.7 42 8.0 28 14.4 100 8.8

All nonmetro : 60 4.2 29 7.8 11 13.9 100 6.3

II Eîfort equals local government taxes and user charges (excluding utility and liquor store receipts) expressed as a

percentage of local resident personal income.

explanation Is that variations in economic base and government responsibilities

can lead to diverse fiscal conditions (these factors are discussed in detail

later in this report). Another explanation is that other factors, including

local attitudes toward public services, may vary widely among totally rural

areas and cause revenue effort to vary. Because totally rural counties are

more numerous in some regions than others, some of the observed statistical

differences between totally rural and less rural areas may merely reflect more

general regional differences. 12/

The West is the region most characterized by very high revenue effort (fig, 2).

About 28 percent of Western nonmetro counties had very high effort, more than

twice the 12-percent frequency of counties with very high effort in the North

Central region and more than five times the 5-percent frequency of counties

with very high effort in the South. Over 50 percent of the nonmetro counties

in the Northeast had low (lower than average) revenue effort, while almost 80

percent of the Southern nonmetro counties had low effort. The South exhibited

the greatest contrast between high and low efforts. Revenue effort in Southern

areas with very high effort averaged 15.7 percent of income, whereas effort in

Southern areas with low effort averaged only 3.8 percent of income.

12/ Over a third of the Nation*s totally rural counties are located in the

North Central region.
Figure 2

Nonmetro Counties with High Revenue Efforts in 1977

Revenue efforts

Very high

Moderately high

Low; includes all

metro counties
Income differences may explain some regional differences. Because of

population size economies, lightly populated rural areas in the West are

expected to have higher revenue effort than are the more densely populated

areas of the rural South. Political and socioeconomic factors may account for

some differences. Differences in the allocation of responsibilities among

State and local levels of government could also lead to regional differences.

Regardless of the source of regional effort differences, the magnitude of these

differences is large, making this topic worthy of further research.

TRENDS IN REVENUE EFFORT

Public reaction to growing taxes may have contributed to California's

Proposition 13 and other recently created fiscal restraints. Although such

legislation may reduce tax burdens, it also reduces the fiscal flexibility of

local governments. Some rural areas are more likely to experience tax

resistance than others. Places with rapidly growing revenue effort are more

likely to be subjected to new tax limitations or to be constrained by existing

limitations. Because new tax limitations often follow a period of rising tax

burdens, examining trends in revenue effort in the seventies may help identify

fiscal trouble spots in the eighties.

Although the percentage of personal income going to local governments declined

in most nonmetro counties from 1972 to 1977, revenue effort rose in 39 percent

of nonmetro counties; 6 percent had rapidly rising effort, whereas the other 33

percent had slowly rising effort (table 2). 13/

Rapidly rising effort was generally more prevalent and rose more rapidly for

totally rural and nonadjacent areas than fror less rural and adjacent areas.

About 14 percent of totally rural nonadjacent areas had rapidly rising revenue

effort, with an average increase of about 7 percent of income (fig. 3). Only 1

percent of urbanized adjacent areas had rapidly rising revenue effort, with an

average Increase of less than 3 percent of income.

Taxpayers in less urbanized areas were most likely to benefit from reduced

fiscal pressure during the midseventies. About two-thirds of less urbanized

areas had declining effort. Metro-adjacent areas were more likely to have

declining effort than nonadjacent areas, regardless of their degree of

rurality. Although least likely to have declining effort, those totally rural

nonadjacent areas with declining effort had the largest average decline, 1.6

percent of income. Thus, totally rural nonadjacent areas exhibit much fiscal

diversity, with both the largest average Increase in revenue effort for areas

with rapidly rising effort and the largest average decrease In revenue effort

for areas with declining effort.

Tlie West was most affected by rapidly rising revenue effort (fig. 4). Although

3-6 percent of counties In the other three regions had rapidly rising effort,

13 percent of Western counties demonstrated this form of fiscal pressure. The

South also showed signs of unusual stress related to rising revenue effort.

13/ The standard deviation for the change In effort (Including both

Increases and decreases) for nometro areas was 2.7 percent of Income during

this period. Counties whose revenue effort rose by at least 2.7 percent of

Income are defined as having rapidly rising effort. Counties whose effort rose

during the period, but by less than 2,7 percent of Income, are defined as

having slowly rising effort.
Tabla 2—Revenue effort trends, for iKsmetro county areas, 1911-11 1/

: Declining effort Slowly rising effort : Rapidly rising effort Î All areas

Area : Share : Average Share : Average Î Share : Average \ Share : Average

: of : change of : change : of : change : of : change

: counties ": in effort counties : in effort : counties : In effort ' counties: in effort

Percent

Urbanized adjaœnt : 66 -0.9 33 0.8 1 2.9 100 -0.3

Urbanized nonadjacent : 61 -1.1 37 .8 2 3.7 100 -.3

Less urbanized

adjacent 67 -1.3 32 .8 2 4.0 100 -.5

Less urbanized

nacîadjaœnt : 64 -1.3 32 .8 4 4.5 100 -.4

Totally rural

adjacent 56 -1.2 33 .9 11 5.5 100 .2

Totally rural

nonadjacent : 51 -1.6 35 1.0 14 6.9 100 .5

Region: :

Northeast : 62 -1.0 35 .8 3 4.2 100 -.2

North Central : 69 -1.6 25 1.0 6 4.7 100 -.6

South : 56 -la 39 .8 5 7.0 100 .0

Wfest : 54 -1.2 33 1.0 13 6.2 100 .5

All nonmetro 61 -1.3 33 .9 6 5.9 100 -.1

1/ Change In effort equals 1977 effort minus 1972 effort.

Figure 3

Percentage of Counties with Rising Revenue Effort, 1972-77

by Type of Rural Area

% of counties

60

40

20

uy////A Adjacent Nonadjacent

Urbanized Less urbanized

— Slowly rising

effort

Totally rural
Figure 4

Nonmetro Counties with Rising Revenue Efforts, 1972-77

Revenue efforts

Rapidly rising

Slowly rising

Falling; includes all

metro counties
Although only 5 percent of Southern counties had rapidly rising effort, the

average increase in effort for these counties was 7 percent of income, more

than that in other regions. In addition, 39 percent of Southern counties had

slowly rising effort, more than that in other regions. In contrast, declining

effort was most evident in the North Central region, where almost 70 percent of

the counties had declining effort• The average decline in these counties was

U6 percent of income, more than that in other regions.

Effects of Population Change

The relatively large average increase in revenue effort for rapidly growing

regions such as the South and West raises an important question. Is rising

revenue effort an expected public service response to population growth? This

question is important not only for what it implies about the cause of rising

revenue effort but also for what it implies about the significance of rising

revenue effort as an indicator of fiscal pressure. If revenue effort is shown

to rise as a normal response to nonmetro population growth, then rising revenue

effort may signify progress rather than indicate fiscal difficulty.

Population growth might be associated with rising revenue effort for several

reasons. To accommodate new firms and industries locating in nonmetro areas,

local governments often must increase their revenues to finance new public

infrastructure. When government revenues and expenditures grow more rapidly

than do local tax bases, revenue effort rises, causing fiscal stress in extreme

cases (9_, p. 17). Rising revenue effort may also be related to the

characteristics of new migrants to rural areas. Because recent migrants often

come from cities where more public services are provided, they may demand more

public goods and services than do long-term residents, boosting revenue effort.

However, there is a strong argument for associating rising effort with

population decline. Because some government costs cannot be reduced from one

year to the next (fixed costs), governments losing population may be unable to

cut costs proportionately. As a result, government revenue effort in the short

run is expected to rise as population falls. In the long run, governments may

reduce their fixed costs in declining areas, but revenue effort may still rise

because of diseconomies associated with smaller population size and density (3

p. 22).

To assess the relationship between trends in revenue effort and population

growth and decline, one may calculate these trends for various population

categories. In this report, I examine three population change categories:

(1) declining areas, (2) stable areas, and (3) growing areas. \AJ Among

nonmetro counties that lost population during the midseventies~the average

revenue effort did not change. Average effort declined 0.2 percent of income

in the stable population category (table 3). In growing counties, revenue

effort declined only 0.1 percent of income on average. These overall

differences are slight, but they suggest that population decline contributes

more to fiscal pressure than does population growth, whereas stable population

appears to reduce fiscal pressure.

Specific types of rural areas exhibited more pronounced differences. Effort in

declining, totally rural areas increased on average about 0.8 percent of

14/ Declining areas were those where population declined by 2 percent or

more from 1972 to 1977. Stable areas neither grew nor declined by more than 2

percent. Growing areas grew 2 percent or more.

10
Table 3—Trards In revenue effort for nonn^tro are^, by population change 1/

Declining population Stable population Rising potxilation All areas

Area : Share Average Share Average Share : Average : Share . Average

of I change : of change of : change of : change

counties ' in effort : counties ' in effort counties : in effort counties : in effort

Percent

Urbanized adjacent 10 -0,3 22 -0,3 67 -0.3 100 -0.3

Urban!zed

nonadjarent 14 -A 23 -.7 63 -.2 100 -.3

Less urbanized

adjacent 11 -.8 23 "*6 66 -.5 100 -.5

Less urbanized

rwnadjacent 15 -.6 25 -J 60 -.2 100 -.4

Totally rural

adjaœnt 9 .8 19 A 72 .2 100 .2

Totally rural

TK>nadjacent 23 .8 17 .9 60 .3 100 .5

Region:

NDrtbeast : 11 -.2 27 A 62 -.4 100 -.2

North Central : 23 -.5 30 -.5 47 -.7 100 -.6

South : 11 .5 17 -a 71 .0 100 .0

\test : 9 1.7 13 •6 79 .3 100 .5

All nonmetro : 15 .0 22 -.2 63 -A 100 -.1

1/ Change in effort equals 1977 effort minus 1972 effort.

income, while effort in growing, totally rural areas increased on average

0.2-0.3 percent of income. Differences between declining and growing areas

were greater for rural areas in the West, where average effort rose 1.7 percent

of income for declining counties compared with 0.3 percent for growing

counties. Thus, population decline, rather than population growth, is associated with rising effort in the West, the region where revenue effort rose most.

Effects of Income Change

The fact that both growing and declining areas in the West had rising revenue

effort suggests that factors other than population change are associated with

rising effort in the West. One such factor is income change. An increase in

the income level of a community can be associated with either an increase or a

decrease in revenue effort. For example, an increase in income can be indirectly associated with rising revenue effort if higher incomes lead residents

to demand substantially more public services. 15/ However, it may take some

time before these demands raise government expenditures. Moreover, if the

15/ Some empirical studies of the income elasticity of demand for public

services support this hypothesis (j^, pp. 91-94).

11
Increase in income is viewed as only a temporary fluctuation, demands for

public services are not likely to rise. In fact, such an increase in income

would directly reduce the effort ratio, at least in the short run, because it

increases the denominator of the revenue effort ratio. This argument implies

that a decrease in income will increase revenue effort, at least in the short

run.

Such an inverse relationship between effort and income trends occurred during

1972-77. Revenue effort increased 2.0 percent of income for the average

nonmetro county in the declining income category, and it decreased 0.4 percent

of income for the average county in the growing income category (table 4). 16/

Income effects were particularly large for totally rural nonadjacent areas,

where revenue effort rose 2.4 percent of income for declining income counties

and declined 0.1 percent of income for growing income counties (fig. 5).

Moreover, income decline was quite common in these areas; 24 percent of totally

rural nonadjacent counties were in the declining income category.

16/ Declining income areas were those where real per capita income declined

by 2 percent or more from 1972 to 1977. Stable income areas had real per

capita Incomes which neither grew nor declined by more than 2 percent. Growing

income areas had real per capita Income growth of 2 percent or more.

Table 4—^Trends in revenue effort for nonmetro county ^"eas, by income change 1/

Declining income : Stable income : Rising income : All areas

Area Share : Average : Share : Average : Share : Average : Share : Average

: of : change I of t change : of : change : of : change

counties : in effort : counties : in effort , counties : in effort :counties : in effort

îfeircent

urbanized adjacent I 2 0.5 2 1.0 95 -0.4 100 -0.3

Ifcbanized iKsnadjacent 2 .7 3 .6 95 -.3 100 -.3

L^s inrbanized adjacent 2 J 4 .3 94 -.6 100 -.5

Less urbanized nonadjacacit 5 1.1 5 .3 89 -.5 100 -.4

Totally rural adjacent 12 2.2 8 .6 80 -.1 100 .2

Totally rural nonadjacait ' 24 2.4 9 -.1 66 -.1 100 .5

Region:

îfortheast 6 .8 8 .2 86 -.3 100 -.2

North Central 14 1.5 6 -.3 80 -1.0 100 -.6

South 3 2.7 4 .8 92 -.1 100 0

W^t : 17 2.9 11 .2 72 -.2 100 .5

All nonmetro 9 2.0 6 .2 85 -.4 100 -.1

1/ Change in effort equals 1977 effort minus 1972 effort.

12
Figure 5

Average Change in Effort 1972-77, by Income Growth/Decline Category and

Rural and Regional Area

Growing income area Urbanized

adjacent

Urbanized

nonadjacent ^

Less urbanized

adjacent

Less urbanized

nonadjacent

i^ Totaliy rural

adjacent

Totaily rural

nonadjacent

Northeast

Nortli Central

South

West

-2 -1 0

Average change in effort (% of income)

Declining income area

0 1 2

Average change in effort (% of income)

The North Central and Western regions were affected most by income changes. In

the North Central region, 80 percent of the nonmetro areas were in the growing

income category, with an average decrease in revenue effort of 1.0 percent of

income. This figure contrasts with a 1.5-percent increase in effort for

declining income areas in the North Central region. In the West, a relatively

large proportion of nonmetro counties—17 percent—^were in the declining income

category, with an average increase in revenue effort of 2.9 percent of income.

This figure contrasts to a 0.1-percent decline in effort for growing income

areas in the West.

The finding that rising revenue effort in totally rural areas and in Western

nonmetro areas is associated with income decline—and to a lesser extent with

population decline—may refute the notion that rising revenue effort reflects

improving socioeconomic conditions associated with the rural turnaround. This

finding demonstrates that rising revenue effort implies growing fiscal

pressure, at least for the 1972-77 period. 17/

TTJ This conclusion leaves open the possibility that over a longer period

risTng effort may reflect socioeconomic improvements related to population and

income growth.

13
PLACES WITH HIGH AND RISING REVENUE EFFORT

Fiscal pressure may be most troublesome when a county has both high and rising

revenue effort, 18/ In 1977, 40 percent of nonmetro counties had high revenue

efforts; 39 percent had rising effort from 1972 to 1977* 19/ If we combine

these two factors, we find that 22 percent of nonmetro counties containing 16

percent of nonmetro population had both high and rising revenue effort.

Average effort for these counties was 10.5 percent of income, more than 4

percentage points above the average for all nonmetro counties. The increase in

revenue effort over the 1972-77 period for the average county with high and

rising effort was 2.5 percent of income. In contrast, effort declined by an

average of 0.1 percent for all nonmetro counties (table 5).

18/ This method of measuring fiscal pressure is similar, but not identical,

to that which the Advisory Commission on Intergovernmental _Relations used when it

employed the level and change in "adjusted" tax effort to indicate a "fiscal

blood pressure" for the 50 States (11).

19/ In this case, "high" means higher than the average effort for all

nonmetro counties. The average effort for all nonmetro counties (excluding

Alaska) was 6.3 percent of income. A county is judged to have rising effort if

its effort increased in absolute value from 1972 to 1977, which occurs whenever

own general revenue rises relative to local income.

Table 5—Nonmetro county areas with high and risirig efforts j7

I Nonmetro couni^ areas mth hi^ and rising efforts

I Share : 1977 : Share Average : Average

Area ' Camties of : poïxilation of effort. : increase

counties 1 Population ; 1977 : in effort,

: 1972-77

: Number Percent "niousands - Percent -

Urbanized adjacent : 26 16 1,922 16 8.3 1.1

Urbanized nonadjacent : 24 16 1,240 15 8.3 1.4

less urbanized adjacent 83 20 2,184 16 8.3 1.4

Less urbanized nonadjacent : 151 21 2,260 17 9.2 1.6

Totally rural adjacent ; 53 21 326 13 11.8 3.6

Totally rural nonadjacent 201 34 971 23 12.5 3.6

Region:

Northeast : 28 24 1,727 25 9.5 1.3

North Cfentral 225 26 2,593 15 9.9 1.9

South 157 14 2,976 13 9.9 3.1

fest 128 37 1,615 23 12.4 3.0

AUL nonmetro : 538 22 8,912 16 10.5 2.5

1/ The statistics provided here refer to counties having revenue effort above 6.3 percent of incone—the

nonmetro average in 1977—land having an increase in revenue effort from 1972 to 1977. Percentage of counties and

percentage of population statistics relate high and rising effort counties to all camties within a geographic

area.

14
The most distressed category is the totally rural nonadjacent category« Over a

third (34 percent) of these areas had high and rising revenue effort, more than

double the percentage of counties with high and rising effort in less rural

areas (fig* 6). These distressed totally rural nonadjacent areas had the

highest average effort (12*5 percent of income); they tied with totally rural

adjacent areas in having the highest average increase in effort (3.6 percent of

income). However s the incidence of counties with high and rising effort is

clearly lower among adjacent, totally rural counties. Only 21 percent of these

counties (containing only 13 percent of the population of all totally rural

adjacent areas) are fiscally distressed. There was no such dramatic difference

between adjacent and nonadjacent areas in urbanized and less urbanized nonmetro

areas.

Regional variations are equally striking. The Incidence of high and rising

effort among nonmetro counties is highest in the West and lowest in the South;

37 percent of Western nonmetro counties had high and rising revenue effort

(fig. 7). Areas in the West had particularly high levels of revenue effort,

averaging 12.4 percent of income. The South had relatively few counties with

high and rising effort (13 percent), but these counties had the highest average

increase in effort, 3.1 percent of income from 1972 to 1977.

Although roughly a quarter of the nonmetro counties in the Northeast and North

Central regions had high and rising revenue effort, the average increase was

less than that in other regions. The Northeast had the largest share of

nonmetro population residing in areas of high and rising revenue effort (25

percent), but it had the lowest average effort for these fiscally distressed

areas.

IMPERFECTIONS IN THE MEASURE OF REVENUE EFFORT

When assessing the significance of geographical differences, one must recognize

that revenue effort is an imperfect indicator of fiscal pressure. In this

section, I examine some of the imperfections which are most likely to affect

fiscal comparisons among types of rural areas and among regions.

Figure 6

Percentage of Counties with High and Rising Effort by Type of Rural Area, 1977

% of counties

40

30

20

10

Adjacent Nonadjacent

Urbanized Less urbanized Totally rural

15
Figure 7

Nonmetro Counties with High and Rising Revenue Efforts, 1972-77

Revenue efforts

High and rising

Other; includes all

metro counties
Local Government Responsibilities

Comparisons of revenue effort among localities can be misleading when local

government tax and spending responsibilities differ substantially. Â local

government with extensive fiscal responsibilities will probably have higher

revenue effort than one with narrow responsibilities. However, a community

with fewer local government responsibilities does not necessarily experience

less fiscal pressure because, when a local government does not assume fiscal

responsibility s local residents must often pay for such services in other ways«

Revenue effort does not count these public service costs to the community;

hence, the measure is imperfect since it understates the fiscal pressure for

counties with fewer local government responsibilities.

Some communities rely heavily on the private sector to provide specific

services, whereas other communities rely on local government. Trash collection

is an example. Other factors being equal, local revenue effort is higher in a

community where government employees collect trash than in a community where

private firms provide this service directly to residents. Note that, although

revenue effort differs, the cost to both types of communities may be the same.

Consequently, when revenue effort between the two types of communities is

compared, the fiscal pressure on communities relying heavily on private-sector

service delivery will be understated by local revenue effort.

Another problem in comparing local responsibility concerns government use of

volunteer labor. Some rural communities make extensive use of volunteer labor

for fire protection. Revenue effort in these communities is expected to be

lower than in others because local government revenues do not reflect the cost

of volunteer effort. But, if other factors are equal, the actual effort of

both communities is similar. Only the form of the effort (paid versus not paid)

differs. Hence, revenue effort understates the pressure on communities making

heavy use of volunteers.

Comparisons of local government effort may also be misleading when interstate

variations in the functional responsibilities of State and local governments

are significant. For example, local revenue effort will be lower in States

where the State government provides local roads than in States where this

responsibility is left to local governments. But, if other factors are equal,

the total cost of local roads to local residents should be similar in both

types of States; only the breakdown between State and local taxes would differ.

Hence, fiscal pressure is understated by local revenue effort in States

providing a large lare of public services to local areas.

Lacking data on government use of volunteer labor and privately provided

services, one can only speculate on the effect of these factors on revenue

effort. Conventional wisdom suggests that volunteer labor is more prevalent in

highly rural areas; thus, one might expect revenue effort to understate the

actual effort of these areas. However, economic considerations such as

population threshold levels suggest that highly rural areas rely on

private-sector provision of public services less than other rural areas,

causing government revenue effort to overstate fiscal pressure. The net effect

of these two factors on interlocal comparisons of revenue effort is not

obvious.

One can get some idea of the regional nature of the comparability problem

associated with differing State assignments of functional responsibility by

examining State government shares of total State and local revenues in each

17
State. 20/ The South is the region most characterized by high State revenue

responsibility (fig. 8), All but two Southern States had high (above average)

State revenue-raising responsibility in 1911* This fact implies that fiscal

pressure is understated by local revenue effort in the South. This tendency

for local government to have less responsibility in the South than in other

regions may partly explain why the South has less revenue effort* In contrast,

almost half the Western States had low (below average) State revenue raising

responsibility. This statistic tends to inflate local revenue effort in the

West, exaggerating the difference between the West and the South,

This imperfection in the measure of revenue effort is particularly noticeable

when most counties in one State have high effort while most counties in a

neighboring State have low effort* For example, the absence of counties with

high effort in Maine and New Mexico is conspicuous, given the high effort in

neighboring States (fig. 2). When compared with neighboring States, Maine and

New Mexico have extremely high State revenue responsibility—66 percent and 78

percent, respectively. These and other examples suggest that comparisons of

local revenue effort among States can be misleading.

Low-Income Communities

Going back to Adam Smith, economists have argued that a proportional tax system

is unfair because it applies a constant tax rate to all Income classes, which

overburdens low-income individuals who have little income available for paying

20/ This is only one of a number of possible indicators one could choose to

represent State versus local responsibilities. For other examples, see (2^, pp.

33-35).

Figure 8

State Revenue Responsibility, 1977^

Below average 2

Above average -

^ Percentage of State-local own general revenues raised by State governments in FY 1977.

^ U.S. average = 45.7 percent,
taxes after spending most of their income on subsistence (7^, p« 95). According

to this logic, a progressive tax system, which applies progressively higher tax

rates with increasing income levels, is prescribed to distribute the tax burden

equitably among rich and poor. Á similar argument can be made that revenue

effort as a proportional measure of fiscal burden understates the fiscal

pressure on low-income communities compared with high-income communities (6,

pp. 75-76). Because of this problem, the Federal General Revenue Sharing

formula uses both tax effort and relative income to distribute funds to

fiscally distressed areas C^^, pp. 4-7).

A logical result of this difficulty with measuring revenue effort is that,

other things being equal, rich communities can maintain higher revenue effort

than poor communities—without necessarily incurring greater fiscal pressure.

Presumably, such differences in income-related effort reflect limitations of

the revenue effort measure rather than real differences in fiscal pressure.

One can get a rough idea of the potential significance of this limitation by

examining average revenue effort for high-, medium-, and low-income counties.

The average effort for nonmetro counties in the low-income category (1977 per

capita income less than $5,000) was 5.6 percent of income in 1977. Mediumincome counties (per capita income between $5,000 and $7,000) had a higher

average effort, 6.6 percent. High-income counties (per capita income greater

than $7,000) had the highest average effort, 7.6 percent. Assuming this

pattern does not result merely from greater preferences for public goods in

higher income communities, these figures suggest that fiscal pressure may be

substantially understated by revenue effort for low-income areas. 21/

This distortion appears greater for some types of rural areas than for others.

All six categories of rural areas exhibited lower average effort in low-income

areas than in medium- and high-income areas (table 6). However, the magnitude

of this income effect on revenue effort varies substantially, depending on the

type of rural area. For adjacent areas, the average difference in revenue

effort between low- and high-income areas is about 1.5 percent of income. For

nonadjacent areas, this difference varies by degree of rurality; it is over 4

percent of income for totally rural areas, over 2 percent for less urbanized

areas, and only 0.5 percent for urbanized areas.

The distortion associated with low incomes appears to cause the differences in

fiscal pressure between totally rural, less urbanized, and urbaaized areas to

be understated by observed revenue effort. Figure 9 compares effort among

nonadjacent rural areas within three income classes. Regardless of the income

level, totally rural areas have distinctly higher revenue effort on average

than do urbanized areas. However, in the low-income class, the difference in

effort between totally rural and urbanized areas is smaller, and there is

little difference between less urbanized and totally rural areas. 22/

21/ Because high-income communities tend to be better educated, the argument

that high-income communities may have acquired greater preferences for public

goods and services than low-income communities may be justified. However,

there is also good reason to believe that low-income communities would prefer

public goods, such as health, education, and welfare assistance, over

nonsubsistence private goods.

22/ One possible explanation for this pattern is that totally rural areas

with low incomes may have to forgo some important government services that are

normally provided by totally rural areas with high Incomes. Because of

economies of scale, the cost of providing these services may be cheaper in

urbanized areas, allowing both rich and poor areas to provide them.

19
Table 6—Revenue effort levels for noTmetro cojnty areas, hy income category IJ

: hem Lncome : Medium Income : Hi^ income : All areas

Area I Share : Average : Share : Average : Share : Average : Share : Average

r of t effort of : effort : of : effort : of : effort

I counties • counties : counties : counties :

Percent

Urbaidzed adjacent : 10 5.0 72 5.8 18 6.3 100 5.8

Urbanized tKmadjacent I 12 5.4 77 5.8 12 5.9 100 5.7

Less urbanized adjacent 28 4.9 62 5.5 10 6.3 100 5.4

Less urbanized

nonadjacent I 33 5.3 56 6.6 11 7.5 100 6.3

Totally rural adjacent : 53 5.0 41 7.1 6 6.4 100 6.0

Totally rural

ncxiadjacent 51 6.3 39 8.8 10 10.5 100 7.7

R^on: :

Ifortbeast : 13 6.5 82 6.4 5 9.0 100 6.5

North Central 20 6.7 64 7.0 16 7.3 100 7.0

South : 53 4.6 41 5.2 5 7.4 100 5.0

Ifest : 24 10.1 60 8.4 15 8.6 100 8.8

AH notmetro ; 35 5.6 54 6.6 11 7.6 100 6.3

j7 Effort equals local govemnent taxes and user clergés (excluding utility and llquior store reœipts) ej^ressed

as a percentage of local personal incane.

Figure 9

Average Effort of Nonadjacent Areas, by Income and Type of Rural Area, 1977

% of income

12

10

8

6

4

2

0

Totally rural

Less urbanized

Urbanized I

Low income Medium income High income

20
Over half the totally rural counties have low Incomes, whereas only about 10

percent of urbanized counties have low incomes (table 3). Therefore, fiscal

pressure is more likely to be understated in totally rural areas than in

urbanized and less urbanized areas. Hence, this income-related distortion

appears to understate substantially the gap in fiscal pressure between highly

rural and less rural areas.

For the same reason, comparisons are probably distorted when revenue effort in

different regions is compared. Over half the Southern rural counties had low

incomes; their average effort was 4.6 percent of income, well below the

average, suggesting that because of low income, revenue effort understates

considerably fiscal pressure in the South. Other things being equal, the

effort difference between the West and the South will be exaggerated.

Tax Exporting

Tax exporting occurs when a Jurisdiction imposes taxes which are largely passed

on to taxpayers residing in other jurisdictions, thus enabling the

tax-exporting jurisdiction to substantially increase its revenues without

unduly pressuring its residents. For example, many rural areas export part of

their property taxes to nonresident property owners, such as urban residents

who own cottages or other property in rural areas and who pay property taxes to

rural jurisdictions (10, p. 38). In farming areas where nonresident-owned

farms are common, residents may export part of their property tax burden

through taxes on these farms. Local property taxes on multlcounty mining,

timber, and power companies can bring additional property tax revenues into

local jurisdictions, without necessarily boosting taxes for local residents.

Jurisdictions can also use nonproperty taxes to export local tax burdens to

nonresidents. Tourist areas export motel and restaurant taxes to visitors.

Regional shopping towns export local sales taxes to residents of surrounding

areas. 23/ Using local sales taxes and user fees, farming areas may shift part

of their~taxes to migrant farmworkers, and border towns may shift taxes to

aliens. 24/ These exported taxes also Inflate the measured local revenue

effort, overstating the fiscal strain on the community. 25/ Because exported

taxes are included in local revenue effort, the measures of revenue effort

substantially overstate the fiscal pressure on residents of some lightly

populated areas which get a large proportion of their revenues from exported

taxes. This situation probably causes fiscal pressure to be overstated most in

the West, the region characterized to the greatest degree by lightly populated

areas with extensive mining and other resource-extraction Industries owned by

nonresident corporate stockholders.

The reverse of tax exporting is tax importing, a phenomenon probably affecting

metro-adjacent rural areas more than nonadjacent rural areas. Tax importing

occurs when residents of a community pay taxes to other jurisdictions.

23/ Fart of the business property taxes on retail establishments may also be

passed on to nonresidents in the form of higher retail prices.

24/ Property taxes can also be passed on to migrant farmers in the form of

higher charges for food and shelter provided by farm operators.

25/ State government taxes represent an important exception. Although

exported State taxes exaggerate State revenue effort, they may actually depress

local revenue effort if the revenues from a State government tax, such as a

severance tax on coal which is exported to residents of other States, are

shared with local jurisdictions.

21
Commuters residing in adjacent nonmetro areas may pay substantial local sales

taxes, excise taxes, highway and transportation user charges, and other taxes

to the metro jurisdictions where they work. Tax importing also occurs when

rural residents visit or shop in neighboring metro areas and pay taxes, such as

local sales and excise taxes, during their visits^ Because these taxes are

borne by rural residents but are not counted in rural revenue effort, local

revenue efforts are expected to understate fiscal preassure for metro-adjacent

areas.

Findings of Regression Analysis

Multiple-regression analysis is a statistical procedure used here to estimate

the independent effects of region and degree of rurality on local revenue

effort» By including variables representing three kinds of measurement

imperfections—local government responsibility, income level, and tax-exporting

factors—one can statistically separate the effects of these variables from the

effects of region and rurality. This separation enables more meaningful

comparisons of revenue effort among regions and rural types.

The statistical appendix of this report presents an analysis of several

regressions. Each regression includes regional and rural identification

variables (dummy variables). The analysis focuses on how the estimated effects

(coefficients) of these variables change when dlstortionary effects are netted

out by the addition of tax exporting, income level, and government

responsibility variables to the regression.

Because direct tax data on the extent of tax exporting are unavailable, I use

economic base variables to represent tax exporting. The percentage of local

employment in mining, farming, retail, and other potential tax-exporting

activities are used as tax-exporting indicators. Metro-adjacency (a dummy

variable) represents potential tax importing from metro areas. Per capita

income represents local income level. A variable measuring the State

government share of State and local revenues represents local government

responsibilities.

I computed the regressions using 1977 data for all nonmetro counties, excluding

Alaska. I concluded that the revenue effort differences among regions and

types of rural areas were statistically significant after the effects of

dlstortionary factors were netted out of effort comparisons. However, some

significant distortions were identified.

The economic base indicators associated with tax exporting were statistically

significant in adding to the revenue effort of nonmetro local governments. The

largest addition to revenue effort (and, therefore, the largest potential

distortion) is associated with farming areas thought to export taxes to

nonresident farmowners and workers. 26/ Tax exporting was also indicated for

mining and retail employment variables, which had a statistically significant

positive effect on revenue efforts. 27/ Metro-adjacency had a statistically

significant negative effect on revenue effort, which indicates tax importing.

26/ The economic base variable used to represent these farming areas Is

nonproprietor farm labor as a percentage of total local employment. This

variable is probably associated with nonresident-owned farms using hired farmworkers or with farms using nonresident migrant workers.

27/ Note that the mining variable was also positively associated with rising

effort in regressions computed for the change in effort between 1972 and 1977.

22
The regression coefficients for regional and rural variables change when

tax-exporting and -importing variables are added to the regression. Analysis

of the changes in these coefficients suggests that tax exporting and tax

importing cause revenue effort to considerably overstate the fiscal pressure on

residents of Western counties. This distortion is partly offset by the

distortion associated with differing State revenue responsibilities which

depresses the effort of Western and Southern counties. Differences in tax

exporting (and importing) and government responsibilities cause revenue effort

to exaggerate the fiscal pressure in totally rural areas. However, this

distortion is mitigated somewhat by low income which depresses revenue effort

in totally rural areas. The fiscal pressure in the South is similarly

understated by local revenue effort because of the depressing effect of low

incomes in the region.

The net effect of these distortions is that simple comparisons of revenue

effort probably exaggerate the variations in fiscal pressure among regions and

types of rural areas. The regression analysis suggests that about half of the

effort gap between regions (West versus South) and about a third of the gap

between rural types (totally rural versus urbanized) disappear when the effects

of local government responsibilities, income levels, and tax importing and

exporting are netted out. Still, many of the differences among regions and

types of rural areas remain after these potential distortions are netted out.

Thus, the basic findings of this report are valid.

These findings underscore the need for caution when one uses revenue effort to

infer local fiscal pressure. This caveat pertains especially to inferences

about individual counties. Local revenue effort may be an extremely misleading

indicator of fiscal pressure in counties with particularly high or low levels

of local government responsibilities, incomes, or tax exporting and importing.

Only a third of the variation in local revenue effort was "explained" by the

factors examined in this regression analysis. Other factors which might affect

local revenue effort are exceptional public service needs, extraordinary tastes

and preferences for public-sector services. State and local limitations (or the

lack of limitations) on local revenues, expenditures, and debt, and heavy

reliance on volunteer workers to provide public services. Some of these

factors may also cause revenue effort to overstate or understate local

government fiscal pressure.

IMPLICATIONS

The indicators of revenue effort presented in this report highlight the diverse

fiscal problems facing rural America. Rural areas have historically suffered

from uniquely rural fiscal problems associated with diseconomies of small

population size and with population and income decline. However, as most rural

areas have grown in recent years, many communities have become more urban.

These developments have led many rural government researchers to examine the

problems of fiscal adjustment related to population growth, economic recession,

and other issues traditionally associated with urban areas. But if one judges

from their high and rising revenue effort, the most rural nonmetro areas—many

of which still suffer from population and income decline—have pressing fiscal

problems.

Totally rural areas are twice as likely to have high and rising revenue effort

as urbanized nonmetro areas are. Nonadjacent, totally rural areas have the

most fiscal pressure. Compared with urbanized nonmetro areas, they were eight

23
times as likely to have very high levels of revenue effort and seven times as

likely to have rapidly rising effort. Although tax exporting seems to

exaggerate these measures of fiscal pressure, especially in totally rural

areas, it only partly accounts for their high revenue effort. Furthermore,

many highly rural areas are in the South, where low incomes tend to deflate

revenue effort•

Rising revenue effort was associated with population and income decline from

1972 to 1977. Effects of population change were greatest in the West, where

revenue effort rose by 1.7 percent of income in declining areas compared with

only 0.3 percent in growing areas. Population decline also contributed to

rising effort in totally rural areas. Among less rural areas, effort generally

declined, and effort trends differed little between growing and declining

areas. For nonmetro areas, declining real income was the more important factor

explaining growing fiscal pressure. Revenue effort in the average nonmetro

county in the declining-income category increased by 2.0 percent of income,

compared with a 0.4-percent decrease in the income-growth category.

In formulating policies to help fiscally distressed rural communities,

therefore, policymakers should be aware of the unique relationship between

population decline and fiscal stress in highly rural areas. This problem seems

to be associated with diseconomies of small population size and density.

Diseconomies in declining, sparsely populated areas may be particularly severe

in the West, where fiscal pressure is greatest. Thus, Federal and State

policymakers should be concerned with the fiscal problems of highly rural

areas, and their policies should address small size diseconomies, whenever

possible. Policymakers should recognize that places suffering from income

decline experience fiscal pressure associated with rising revenue effort. This

situation may make it difficult for local governments in areas experiencing

economic decline to reverse their economic fortunes through economic

development policies that are locally financed.

With regard to the frostbelt-sunbelt debate, extreme forms of nonmetro fiscal

stress occur primarily in the West and to a lesser extent in the South.

Although Southern fiscal problems manifest themselves chiefly in rising revenue

effort, Western rural areas are more likely to have both high and rising

effort. Although a relatively large share of the nonmetro population in the

Northeast resides in areas with high and rising revenue effort, the fiscal

situation appears bright for most nonmetro areas in the frostbelt. This

perspective differs from that ordinarily associated with sunbelt-frostbelt

comparisons of urban stress. Federal policymakers should consider these

distinctions when dealing with the sunbelt-frostbelt issue.

Revenue effort is generally a useful measure of fiscal pressure in comparisons

among rural areas and regions. However, I found significant distortions

associated with tax exporting and importing, low income, and local government

responsibility for public services. Heavy tax exporting and importing appear

to exaggerate the revenue effort of highly rural areas and the rural West,

overstating the fiscal pressure on these areas. Low incomes depress revenue

effort in highly rural areas and in the rural South, thus understating the

fiscal pressure in these areas. Relatively low responsibilities of local

governments rediace the revenue effort of rural areas in the South and West,

also understating fiscal pressure. While these distortions do not alter the

main findings of this report, one should be cautious when Interpreting revenue

effort in individual counties as an indicator of fiscal pressure, because the

distortions associated with individual counties may be particularly misleading.

24
REFERENCES

(1) Bahl, Roy, Marvin Johnson, and Michael Wasylenko. "State and Local

Government Expenditure Determinants: The Traditional View and a New

Approach," Public Employment and State and Local Government Finance (ed.

Roy Bahl, Jesse Burkhead, and Bernard Jump, Jr.)« Cambridge, MA:

Ballinger Publishing Co., 1980, pp. 65-121.

(2) Bradbury, Katherine L. "Structural Fiscal Distress in Cities: Causes and

Consequences," New England Economic Review, Jan./Feb. 1983, pp. 32-42.

(3) Coelen, Stephen P. "Public Service Delivery in Rural Places," Rural

Development Perspectives. RDP-4. U.S. Dept. of Agr., Econ. Res. Serv.,

Sept. 1981, pp 20-23.

(4) Fox, William F. Size Economies in Local Government Services. RDRR-22.

U.S. Dept. of Agr., Econ. Stat. Coop. Serv., Aug. 1980.

(5) Hines, Fred K., and others. Social and Economic Characteristics of the

Population in Metro and Nonmetro Counties, 1970. AER-272. U.S. Dept of

Agr., Econ. Res. Serv., Mar. 1975.

(6) Maxwell, James A. "The Adequacy of State and Local Tax-Effort," Publius,

Vol. 1, No. 2, 1972, pp. 69-76.

(7) Musgrave, Richard A. The Theory of Public Finance: A Study In Public

Economy. New York: McGraw Hill, Inc., 1959.

(8) Reeder, Richard J. Nonmetropolitan Fiscal Indicators: A Review of the

Literature. Staff Report No. AGES 830908. U.S. Dept. of Agr., Econ. Res.

Serv., Jan. 1984.

(9) Stinson, Thomas F. "Overcoming Impacts of Growth on Local Government

Finance," Rural Development Perspectives. RDP-4. U.S. Dept. of Agr.,

Econ. Res. Serv., Sept. 1981, pp. 12-19.

(10) Stocker, Frederick D. "Fiscal Needs and Resources of Nonmetropolitan

Communities," National Conference on Nonmetropolitan Community Services

Research. Prepared for the Committee on Agriculture, Nutrition, and

Forestry, U.S. Senate, July 12, 1977, pp. 25-41.

(11) U.S. Advisory Commission on Intergovernmental Relations. Measuring the

Fiscal "Blood Pressure" of the States—1964-75. M-111. Washington, DC,

1977.

(12) . The State of State-Local Revenue Sharing. M-121.

Washington, DC, 1980.

(13) U.S. Department of Agriculture, Economic Research Service. "Rural

Indicators—Local Government: Revenue, Expenditures, and ladebtedness,"

Rural Development Perspectives. RDP-4. Sept. 1981, pp. 46-47.

(14) U.S. Geaeral Accounting Office. How Revenue Sharing Formulas Distribute

Aid: Urban-Rural Implications. PAD-80-23. 1980.

25
STATISTICAL APPENDIXî REGRESSION ANALYSIS

This appendix presents a series of multiple regressions designed to identify

and separate out the effects of tax exporting, tax importing, low incomes, and

State revenue responsibilities. I computed four regressions using 2,400 U.S.

nonmetro county areas (excluding Alaska). The dependent variable in each

regression is 1977 revenue effort (local own source general revenues as a

percentage of resident personal income). Independent variables are defined in

appendix table 1. The estimated regression coefficients for each regression

are presented in appendix table 2. The appendix concludes with a brief

discussion of another regression examining the change in revenue effort from

1972 to 1977,

The first regression includes only the five regional and rural classification

variables, which are zero-one dummy variables representing the South, West,

Northeast, totally rural, and urbanized classifications. 1/ Because variables

associated with economic base, metro dependency, income, and State government

revenue responsibility are left out of this regression, one may view the

regression as misspecified and the rural and regional variable coefficients as

distorted (or biased).

The extent of the bias is clearest if one compares the biased rural and

regional coefficients in the first regression with the unbiased coefficients

from the correctly specified fourth regression, which separates out the effects

of variables representing tax exporting and importing, income level, and local

government responsibilities. IJ Bias is most noticeable for the Southern dummy

variable, whose coefficient falls markedly from -1.96 in the first regression

to -0.51 in the fourth regression. This change implies that factors excluded

in the first regression cause Southern revenue effort to be understated by 1.45

percent of income. Northeastern effort is also understated, but to a much

smaller degree. In contrast. Western revenue effort is overstated by 0.35

percent of income. _3/ Thus, the revenue effort gap between South and West is

substantially exaggerated (almost doubled) because of bias inherent in simple

uncorrected comparisons.

Bias also exaggerates the gap between totally rural and urbanized areas. The

coefficient for totally rural areas declines from 1.19 in the first regression

to 0.92 in the fourth regression. This decline implies that fiscal pressure in

IJ Dummy variables representing the North Central region and the less

urbanized nonmetro classification are intentionally excluded to avoid

statistical problems of multlcollinearlty.

IJ The terms unbiased and correctly specified are used only in a relative

sense in reference to the fourth regression. This regression remains

misspecified to the extent that other important variables may be excluded. For

example, highly rural areas are more likely to use volunteer workers than less

rural areas. Because the necessary data are not available, no variable

representing volunteer effort could be included in the regression; hence, the

totally rural regression coefficient remains biased as an indicator of fiscal

pressure.

yf Statistical reasons prevented the Inclusion of a North Central variable

in the regression. The coefficients for each of the regions must be

interpreted as deviations from that of the North Central region. Although this

procedure complicates assessing the bias associated with this region, one can

conclude from the opposite directions of the bias for the West and South that

the magnitude of bias for the North Central region is not large.

25
Appendix table 1—Variable description

Variable Definition IMt Mean Standard

deviation

SOÜffl : 0,1 dunray variable South = 1 0.45 0.49

WEST : 0,1 dunooiy variable Vfest = 1 .14 .35

NDKIHEAST : 0,1 duQBÇ? variable fbrtheast = 1 .05 .21

TSURAL : 0,1 rural dummy variable Totally rural = 1 .35 .47

URBA^S : 0,1 rural dunnçr variable Urbanized = 1 .13 .33

PCINOCME : Resident personal incoine

: per capita jV Thousand 5.5 1.2

imiP : Farm proprietor employment 1/ Bercent of total

local employment 14.4 10.2

FARMNP : Farm ncxiproprietor ecDployment Do 4.8 5.2

NFARMAG : NDnfarm agricultural eraployment Do .6 1.0

MINING Mining employment Do 2.4 6.3

MANÜFAC Î Manufacturing eDDployment Do 15.8 12.7

RETAIL ; Retail enployment Db 10.7 3.9

SERVICE : Services employment Do 11.6 5.9

AÛJ ¡ 0,1 áxjBsay variable Metro adjacent = 1 .4 .5

STÄIESH : State share of State-local

Gwn general revenues,

average for State Percent 57.7 7.4

EFPOKT 2/ : Um source general

revenue effort Percent of income 6.3 3.8

1/ 1977 income, population, and enployment data from U.S. Department of Comadree, Bureau of Eccxrondc Analysis.

2/ Dependent variable in regressions.

27
Appendix table 2—-Regression coefficients

Independent : First : Second : Third : Fourth

variablesl_/ : regression : regression : regression : regression

Coefficient

S0UTH2/ : -1.96* -1.53* -1.66* -0.51*

WEST2/ : 1.82* 1.87 .97* 1.47*

NORTHEAST2/ : -.10 .11 .51* .55*

TRURAL2/ 1.16* 1.39* .99* .92*

URBANZ2_/ : -.37 -.61* -.29 -.14

PCINCOME 4.91* 2.74* 1.63*

FARMP : — -.01 -.01

FARMNP :

— .16* .16*

NFARMAG : — .29* .09

MINING . — — .05* .06*

MANUFAC I —

— -.02* -.02*

RETAIL : — — .08* .09*

SERVICE :

— -.02* -.03*

ADJ2/ :

— -.52* -.59*

STATESH ! — — "" " -"~~ -.17*

CONSTANT : 6.61 3.64 4.23 13.83

R-SQUAREV : .15 .17 .25 .33

—Indicates variable was not in regression.

* Indicates coefficients which are statistically significant at 99-percent

confidence level.

J^/ The dependent variable is 1977 own general revenue effort.

2_/ Zero/one dummy variables are used for region, rural, and metro adjacent

classifications. The North Central, independent, and medium rural

classifications are excluded to avoid multicollinearity.

3/ Adjusted R square statistic.

23
totally rural areas is overstated if one uses simple revenue effort. The

coefficient for urbanized areas rises from -0.37 to -0.14, implying that

revenue effort understates the fiscal pressure in these areas. The net result

is that bias overstates the gap between the two by 0.47 percent of income.

The series of four regressions can be viewed as a progression. The first

regression is uncorrected for bias. The second regression nets out the effect

of low income by adding per capita income as an explanatory variable in the

regression. The third regression is like the second, except that it nets out

the effects of tax exporting (by adding economic base variables) and importing

(by adding a metro-adjacency variable), kj The fourth regression is the same

as the third, except that it also nets out the effect of State revenue

responsibility by adding a revenue responsibility variable to the regression. 5^/

The coefficent change from one regression to the next may be used to indicate

the separate effects associated with each kind of bias.

Between the first and second regressions, for example, the increase from -1.96

to -1.53 in the coefficient for the South implies that low incomes in the South

understate revenue effort by 0.43 percent of income (other things being

equal), hj By far the largest increase in the coefficent for the South,

however, is associated with the fourth regression, which includes the variable

for State revenue responsibility. Apparently, Southern nonmetro areas have low

local revenue effort mainly because large State revenue responsibility is

common to the region.

The overstatement of revenue effort in the West seems to result primarily from

tax-exporting (and tax-importing) bias, which is implied by the decrease in the

~k] The potential for tax exporting is thought to be a function of the local

economic base. Economic base is represented by the percentage of local

employees in five major industrial classificattonss agriculture, mining,

manufacturing, retail, and services. Agriculture is broken down into three

categories: farm proprietors, nonfarm agricultural employees, and farmworkers.

Of these three, tax exporting is expected to be most important where hired farmworkers are relatively important to the local economy. In such places, there

may be greater potential to export property taxes to nonresident proprietors,

and sales taxes and user charges to migrant farmworkers. Retail businesses are

expected to export taxes to nonresident consumers visiting retail sales

centers. Mining industries are expected to export property and severance taxes

to nonresident consumers and stockholders in other States. Manufacturing

industries can export taxes either to consumers or to stockholders, both of

whom are likely to be nonresidents. Hotel and motel services, included in the

services industrial classification, export taxes to tourists. Hence, positive

regression coefficients were expected for these variables.

_5/ The variable added in the fourth regression is the State share of

State-local own general revenues. The State share was computed for each State

based on all local governments within the State, and this share was attributed

identically to each nonmetro county area within the State. This percentage

share variable is expected to be inversely related to local revenue effort as a

higher State share implies higher State tax burdens and, therefore, more

pressure to lower local taxes.

6/ As noted before, a separate variable for the North Central region is not

included in the regression. The coefficients í:or the other regions must,

therefore, be interpreted as deviations from that oÇ the North Central region.

This means that the terms understate and overstate are used here in a relative,

rather than an absolute, sense—that is, relative to the North Central region.

29
coefficent for the West from 1.82 in the second equation to 0.97 in the third

equation. Although this source of bias increases Western revenue effort by

almost 1 percent of income, about 0.5 percent is offset when the relatively low

revenue responsibilities for the Western States are included in the fourth

regression.

The coefficient for the Northeast increases with each subsequent regression;

thus, each type of bias causes Northeastern revenue effort to be understated

slightly, compared with North Central effort (the unspecified control region).

The largest bias for the Northeast is associated with tax exporting, indicated

by the coefficient increase from 0.11 in the second regression to 0.51 in the

third regression.

After the effects of all of these variables which are thought to distort

revenue effort comparisons are netted out, significant variation in regional

effort remains. 2/ ^^om the fourth regression, which is corrected for bias,

one can see that the positive regression coefficient for the Northeast is

larger in absolute value than the negative coefficient for the South. Hence,

after bias factors are netted out, revenue effort in the North Central region

(the control in the regresssion) is more similar to low effort in the South

than to higher effort in the Northeast. The high effort in the West is at the

opposite end of the scale from the low effort in the South, as one can see from

the coefficients for the West and South in the fourth regression. This finding

is interesting because it suggests the fiscal differences between the sunbelt

and frostbelt may be less important than the regional differences within each

category.

The fourth regression also shows the relative importance of the State revenue

responsibility variable which, when added to the other variables in the

regression, increases the explained variation (R-SQUARE) from 25 to 33 percent.

This finding suggests that interstate comparisons of local effort may be

heavily biased. In terras of the addition to explained variation, the extent of

the bias is equivalent to that of tax exporting (and importing).

The relative importance of the individual tax-exporting variables deserves

mention. The most important tax-exporting factor, judged from the size of the

regression coefficients in the fourth regression, is the farmworker variable

(FARMNP), followed by the retail and mining variables. 8/ The negative

coefficients for the manufacturing and services variables are surprising.

Rural areas compete for manufacturing establishments in a way that one might

expect them to export taxes and thereby add to local revenue effort.

Likewise, many service establishments, such as hotels and motels, tax

nonresidents and thereby add to local effort. The surprising negative

coefficients may occur for any number of reasons. One possible explanation for

the manufacturing coefficient is that manufacturing companies locate new plants

in low tax areas and bargain for tax concessions. The services coefficient may

result from private schools, hospitals, and other private-sector services which

may actually substitute for services otherwise provided by local governments.

7J An F-test for statistical significance of explained variation found that

the regional variables were statistically significant at the 99-percent

confidence level.

SJ Nonfarm agricultural employment is ignored because it is not

statistically different from zero.

30
The most important observation is the effect of distortionary factors on the

gap in revenue effort between totally rural and urbanized areas. The totally

rural coefficient increases substantially from the first to the second

regression, suggesting that low incomes depress revenue effort in totally rural

areas. Urbanized areas have higher incomes which add to their revenue effort,

as shown by the decline in the urbanized coefficient between the first and

second regressions. Although adjusting for this source of bias appears to

increase the gap between the two^ the gap is reduced when the effects of tax

exporting and importing are netted out, as is indicated by the change in the

two coefficients from the second to the third regression. Adjusting for this

kind of bias results in a 0.4-decrease in the totally rural coefficient and a

0.32-increase in the urbanized coefficient. Although the net effect of these

distortionary factors is to exaggerate the effort gap between totally rural and

urbanized areas, most of the gap appears to be unrelated to bias factors. 9^/

One should not overlook the fact that the regional and rural factors and the

distortionary factors explain only 33 percent of the variation in nonmetro

revenue effort, as indicated in the R-SQUÂRE statistic for the fourth

regression. This means that most of the variation in local effort relates to

other factors—economic, political, and social. Therefore, research is needed

on the causes for variations in revenue effort.

I used a similar regression approach to explain variations in the change in

effort from 1972 to 1977. The regression was not powerful; only about 15

percent of the variation was explained, and the results are not presented here.

However, there were several notable findings. As expected, population decline

was positively related to growth of local revenue effort. Some economic base

variables, such as the growth of mining and nonfarm agricultural employment,

also contributed significantly to growing revenue effort in nonmetro areas.

The most important explanatory variable in this regression was the change in

per capita income, which was inversely related to the change in revenue effort.

This inverse relationship seems to contradict the earlier finding that effort

level (in 1977) was directly related to per capita income level (in 1977). Two

possible explanations arise. First, the 1972-77 change in income may be

transitory rather than permanent. For example, fluctuations in agricultural

prices do not represent permanent changes in income for farming communities.

Tlius, local government revenues and expenditures may be maintained at roughly

the same levels despite a substantial increase or decrease in income, causing

revenue effort to rise or fall in the short run. Second, the income change may

be permanent, but there may be a time lag in the adjustment of taxes. In

either case, changes in revenue effort would be expected to vary inversely with

income changes in the short run, but not in the long run. Hence, there is no

real contradiction.

It is interesting that when the income change variable is included in the

regression, the difference between the growth of effort in the West and the

South disappears, and the difference between totally rural and urbanized areas

is cut in half. Nevertheless, signLfLeant differences between the sunbelt and

frostbelt and between highly rural and less rural areas remain after one

accounts for changes la population, income, and economic base.

9/ An F-test showed totally rural and urbanized variables were statistically

significant at the 99-perceat confidence level.

31
OTHER REPORTS OF INTEREST ON RURAL ISSUES

Patterns of Change in the Metro and Nonmetro Labor Force, 1976-82 reveals that

nonmetro areasj particularly farm areas, lagged behind metro areas in employment

growth during the 1976-82 period. This reversed a pattern of faster nonmetro growth

occurring in the late sixties and early seventies. RDRR-44. December 1984. 28

pp. t2.00. Order SN: 001-019-00358-8.

Counting Hired Farmworkers; Some Points To Consider concludes that as many as

two-thirds of the Nation's hired farmworkers may not have been counted in the 1980

Decennial census farm labor categories because they were not working on farms in

March when the data were collected. Data from USDA's 1981 Hired Farm Working Force

Survey suggests that the farm labor census data are more likely to describe workers

employed in hired farmwork year round. AER-524. December 1984. 16 pp. $1.00.

Order SN: 001-019-00367-7.

Distribution of Employment Growth in Nine Kentucky Counties; A Case Study shows

that people moving to a nonmetro area held a disproportionate share both of jobs in

growing business establishments and of better paying executive jobs. Manufacturing

was the study area's major economic driving force, but the private service sector

(which provided services to the manufacturing sector and to the area's growing

population) was an important contributor to job growth between 1974 and 1979.

RDRR-41. August 1984. 44 pp. $2.25. Order SN; 001-019-00337-5.

Chartbook of Nonmetro-Metro Trends is a quick check on metro and nonmetro

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Housing of the Rural Elderly finds that the number of rural elderly households rose

16 percent between 1974 and 1979 compared with a 10-percent increase for all U.S.

households, based on the 1979 Annual Housing Survey. Most of the U.S. elderly live

in adequate housing, but 27 percent of the elderly renters and 18 percent of all

elderly living in the South have inadequate housing. In 1979, 15 percent of the

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elderly. RDRR-42. July 1984. 20 pp. $1.50. Order SN: 001-019-00335-9.

Immigration Reform and Agricultural Labor assesses effects of recent legislation

proposing that farm employers hire either American workers or legal foreign

workers. Labor-intensive farms, particularly in vegetable- and fruit-growing States

such as California and Florida, would be most affected by this legislation.

AER-510. April 1984. 36 pp. $2.00. Order SN: 001-000-04411-7.

The Hired Farm Working Force of 1981 examines characteristics and earnings of about

2.5 million hired farmworkers 14 years of age and older. Migrant workers account

for only about 5 percent of all hired farmworkers. Includes over 30 tables.

AER-507. November 1983. 64 pp. $2.00. Order SN; 001-000-04370-6.

A Profile of Female Farmers in America discusses social and economic characteristics

of female farmers, including age, race, size of household, farm and off-farm income,

types of farms female farmers most frequently run, and value of agricultural

products sold. Although the number of U.S. farms is dropping, the number of female

farmers is rising. They tend to run smaller farms and earn less than their male

counterparts. RDRR-45. January 1985. 32 pp. $1.50. Order SN: 001-019-00378-2.

^U.S, GOVERNMENT PRINTING OFFICE : 1985-^60-9^12201OÇ-ERS
Do Bank Size and Metro-Nonmetro Location Affect Bank Behavior? shows that a bank's

lending policies and Its aggressiveness In attracting large deposits depend more on

the size of the bank's assets than on Its rural or urban location. Many rural banks

do, however, take fewer risks than do urban banks, principally because of the small

value of their assets rather than because of their location. April 1985. 20 pp.

$1.00. Order SN: 001-019-00392-8.

Physicians In Nonmetro Areas During the Seventies shows that the gap between the

number of physicians In nonmetro and metro areas widened during the seventies, with

nonmetro areas lagging by almost 100 physicians per 100,000 population. This report

describes availability of physicians In nonmetro areas In light of population

changes and demand for medical care. RDRR-46. March 1985. 28 pp. $1.50. Order

SN: 001-0-19-00380-4.

Farm Population Trends by Farm Characteristics, 1975-80 finds that the number of

persons living on larger farms jumped 67 percent between 1975 and 1980, while

smaller and midsize farms together lost about 20 percent of their population.

Despite the heaviest rates of population loss, smaller farms still contain about

half of the U.S. farm population. Midsize farms lost about 7 percent of their

population during 1975-80 but still contain nearly 33 percent of the U.S. farm

population. Although the number of persons living on larger farms Increased

substantially, they only account for 18 percent of farm residents. RDRR-40.

February 1984. 48 pp. $2.00. Order SN: 001-019-00333-2.

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